DocumentCode :
1184891
Title :
A user pattern learning strategy for managing users´ mobility in UMTS networks
Author :
Quintero, Alejandro
Author_Institution :
Dept. of Comput. Eng., Ecole Polytech. de Montreal, Que., Canada
Volume :
4
Issue :
6
fYear :
2005
Firstpage :
552
Lastpage :
566
Abstract :
Third-generation mobile systems provide access to a wide range of services and enable mobile users to communicate regardless of their geographical location and their roaming characteristics. Due to the growing number of mobile users, global connectivity, and the small size of cells, one of the most critical issues regarding these networks is location management. In recent years, several strategies have been proposed to improve the performance of the location management procedure in 3G mobile networks. In this paper, we present a user pattern learning strategy (UPL) using neural networks to reduce the location update signaling cost by increasing the intelligence of the location procedure in UMTS. This strategy associates to each user a list of cells where she is likely to be with a given probability in each time interval. The implementation of this strategy has been subject to extensive tests. The results obtained confirm the efficiency of UPL in significantly reducing the costs of both location updates and call delivery procedures when compared to the UMTS standard and with other strategies well-known in the literature.
Keywords :
3G mobile communication; learning (artificial intelligence); mobility management (mobile radio); neural nets; telecommunication computing; UMTS network; call delivery procedure; location management; location update signaling; neural network; third-generation mobile system; user mobility management; user pattern learning strategy; 3G mobile communication; Bandwidth; Costs; Databases; Intelligent networks; Mobile radio mobility management; Neural networks; North America; Roaming; Testing; Index Terms- Location update; UMTS neural networks.; mobility management; user pattern learning;
fLanguage :
English
Journal_Title :
Mobile Computing, IEEE Transactions on
Publisher :
ieee
ISSN :
1536-1233
Type :
jour
DOI :
10.1109/TMC.2005.75
Filename :
1516105
Link To Document :
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